Synopsis
Soft Computing and Machine Learning with Python examines various aspects of machine learning with python with a detailed information on soft computing. It includes four different sections, where section 1 and 2 are dedicated towards soft computing theory and machine learning techniques and on the other hand section 3 and 4 are dedicated to the details of python language and machine learning with python. Provides the reader with the insights into the development of python and machine learning, so as to understand the classification multigraph models of secondary RNA structure using graph-theoretic descriptors.
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About the Author
Dr. Zoran Gacovski has earned his PhD degree at Faculty of Electrical engineering, Skopje. His research interests include Intelligent systems and Software engineering, fuzzy systems, graphical models (Petri, Neural and Bayesian networks), and IT security. He has published over 50 journal and conference papers, and he has been reviewer of renowned Journals. In his career he was awarded by Fulbright postdoctoral fellowship (2002) for research stay at Rutgers University, USA. He has also earned best-paper award at the Baltic Olympiad for Automation control (2002), US NSF grant for conducting a specific research in the field of human-computer interaction at Rutgers University, USA (2003), and DAAD grant for research stay at University of Bremen, Germany (2008). Currently, he is a professor in Computer Engineering at European University, Skopje, Macedonia.
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Hardcover. Condition: new. Hardcover. Soft Computing and Machine Learning with Python examines various aspects of machine learning with python with a detailed information on soft computing. It includes four different sections, where section 1 and 2 are dedicated towards soft computing theory and machine learning techniques and on the other hand section 3 and 4 are dedicated to the details of python language and machine learning with python. Provides the reader with the insights into the development of python and machine learning, so as to understand the classification multigraph models of secondary RNA structure using graph-theoretic descriptors. Examines various aspects of machine learning with python, including detailed information on soft computing. Coverage includes soft computing theory and machine learning techniques, the python language, and machine learning with python. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781773615004
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